Overview

Dataset statistics

Number of variables20
Number of observations7321633
Missing cells693
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 GiB
Average record size in memory160.0 B

Variable types

Numeric5
Categorical9
Text6

Alerts

sentPrice is highly overall correlated with winBidHigh correlation
winBid is highly overall correlated with sentPriceHigh correlation
unitDisplayType is highly overall correlated with c1 and 1 other fieldsHigh correlation
bundleId is highly overall correlated with c1 and 3 other fieldsHigh correlation
c1 is highly overall correlated with unitDisplayType and 3 other fieldsHigh correlation
c3 is highly overall correlated with bundleId and 1 other fieldsHigh correlation
size is highly overall correlated with unitDisplayTypeHigh correlation
mediationProviderVersion is highly overall correlated with bundleIdHigh correlation
bidFloorPrice is highly overall correlated with bundleId and 1 other fieldsHigh correlation
bundleId is highly imbalanced (54.0%)Imbalance
c1 is highly imbalanced (50.8%)Imbalance
c3 is highly imbalanced (56.8%)Imbalance
size is highly imbalanced (52.9%)Imbalance
mediationProviderVersion is highly imbalanced (57.6%)Imbalance
bidFloorPrice is highly imbalanced (77.8%)Imbalance
sentPrice is highly skewed (γ1 = 49.61836793)Skewed

Reproduction

Analysis started2023-07-28 11:03:07.729356
Analysis finished2023-07-28 11:07:53.696531
Duration4 minutes and 45.97 seconds
Software versionydata-profiling vv4.3.2
Download configurationconfig.json

Variables

eventTimestamp
Real number (ℝ)

Distinct7302171
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6570445 × 1012
Minimum1.6562901 × 1012
Maximum1.6577589 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:53.782098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6562901 × 1012
5-th percentile1.6564225 × 1012
Q11.6567102 × 1012
median1.6570433 × 1012
Q31.6573883 × 1012
95-th percentile1.6576625 × 1012
Maximum1.6577589 × 1012
Range1.4687966 × 109
Interquartile range (IQR)6.780752 × 108

Descriptive statistics

Standard deviation3.9642434 × 108
Coefficient of variation (CV)0.00023923578
Kurtosis-1.1321931
Mean1.6570445 × 1012
Median Absolute Deviation (MAD)3.3932466 × 108
Skewness-0.021794946
Sum-6.3144722 × 1018
Variance1.5715226 × 1017
MonotonicityNot monotonic
2023-07-28T13:07:53.934757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.657032642 × 10124
 
< 0.1%
1.657311227 × 10123
 
< 0.1%
1.656771117 × 10123
 
< 0.1%
1.656535872 × 10123
 
< 0.1%
1.656482565 × 10123
 
< 0.1%
1.656950652 × 10123
 
< 0.1%
1.656960313 × 10123
 
< 0.1%
1.657667173 × 10123
 
< 0.1%
1.657298556 × 10123
 
< 0.1%
1.657511764 × 10123
 
< 0.1%
Other values (7302161) 7321602
> 99.9%
ValueCountFrequency (%)
1.6562901 × 10121
< 0.1%
1.656290102 × 10121
< 0.1%
1.656290104 × 10121
< 0.1%
1.656290104 × 10121
< 0.1%
1.656290104 × 10121
< 0.1%
1.656290105 × 10121
< 0.1%
1.656290105 × 10121
< 0.1%
1.656290106 × 10121
< 0.1%
1.656290106 × 10121
< 0.1%
1.656290106 × 10121
< 0.1%
ValueCountFrequency (%)
1.657758897 × 10121
< 0.1%
1.657758892 × 10121
< 0.1%
1.657758891 × 10121
< 0.1%
1.657758891 × 10121
< 0.1%
1.657758891 × 10121
< 0.1%
1.657758889 × 10121
< 0.1%
1.657758888 × 10121
< 0.1%
1.657758888 × 10121
< 0.1%
1.657758886 × 10121
< 0.1%
1.657758885 × 10121
< 0.1%

unitDisplayType
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
banner
5785775 
rewarded
848254 
interstitial
687604 

Length

Max length12
Median length6
Mean length6.7951958
Min length6

Characters and Unicode

Total characters49751930
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowbanner
2nd rowbanner
3rd rowbanner
4th rowbanner
5th rowinterstitial

Common Values

ValueCountFrequency (%)
banner 5785775
79.0%
rewarded 848254
 
11.6%
interstitial 687604
 
9.4%

Length

2023-07-28T13:07:54.079211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-28T13:07:54.201338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
banner 5785775
79.0%
rewarded 848254
 
11.6%
interstitial 687604
 
9.4%

Most occurring characters

ValueCountFrequency (%)
n 12259154
24.6%
e 8169887
16.4%
r 8169887
16.4%
a 7321633
14.7%
b 5785775
11.6%
i 2062812
 
4.1%
t 2062812
 
4.1%
d 1696508
 
3.4%
w 848254
 
1.7%
s 687604
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49751930
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 12259154
24.6%
e 8169887
16.4%
r 8169887
16.4%
a 7321633
14.7%
b 5785775
11.6%
i 2062812
 
4.1%
t 2062812
 
4.1%
d 1696508
 
3.4%
w 848254
 
1.7%
s 687604
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 49751930
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 12259154
24.6%
e 8169887
16.4%
r 8169887
16.4%
a 7321633
14.7%
b 5785775
11.6%
i 2062812
 
4.1%
t 2062812
 
4.1%
d 1696508
 
3.4%
w 848254
 
1.7%
s 687604
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49751930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 12259154
24.6%
e 8169887
16.4%
r 8169887
16.4%
a 7321633
14.7%
b 5785775
11.6%
i 2062812
 
4.1%
t 2062812
 
4.1%
d 1696508
 
3.4%
w 848254
 
1.7%
s 687604
 
1.4%
Distinct144
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:54.358263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length7
Mean length6.3239761
Min length2

Characters and Unicode

Total characters46301832
Distinct characters57
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowLG
2nd rowGeneric
3rd rowGeneric
4th rowGeneric
5th rowOPPO
ValueCountFrequency (%)
generic 2088820
28.5%
samsung 1749701
23.9%
apple 1489130
20.3%
motorola 552553
 
7.5%
huawei 362583
 
4.9%
xiaomi 303448
 
4.1%
oppo 153464
 
2.1%
lg 117628
 
1.6%
oneplus 73317
 
1.0%
sharp 49529
 
0.7%
Other values (139) 385172
 
5.3%
2023-07-28T13:07:54.666012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6295721
13.6%
n 4012798
 
8.7%
i 3190450
 
6.9%
a 3106151
 
6.7%
p 3032360
 
6.5%
r 2719969
 
5.9%
l 2239561
 
4.8%
G 2229639
 
4.8%
o 2220022
 
4.8%
u 2212994
 
4.8%
Other values (47) 15042167
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38129596
82.4%
Uppercase Letter 8143793
 
17.6%
Dash Punctuation 19523
 
< 0.1%
Other Punctuation 5161
 
< 0.1%
Space Separator 3712
 
< 0.1%
Decimal Number 47
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 2229639
27.4%
S 1847718
22.7%
A 1527662
18.8%
M 575158
 
7.1%
O 399298
 
4.9%
P 383885
 
4.7%
H 370176
 
4.5%
X 303867
 
3.7%
L 180930
 
2.2%
T 76281
 
0.9%
Other values (16) 249179
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
e 6295721
16.5%
n 4012798
10.5%
i 3190450
8.4%
a 3106151
8.1%
p 3032360
8.0%
r 2719969
 
7.1%
l 2239561
 
5.9%
o 2220022
 
5.8%
u 2212994
 
5.8%
c 2137209
 
5.6%
Other values (15) 6962361
18.3%
Decimal Number
ValueCountFrequency (%)
1 27
57.4%
5 10
 
21.3%
0 10
 
21.3%
Dash Punctuation
ValueCountFrequency (%)
- 19523
100.0%
Other Punctuation
ValueCountFrequency (%)
& 5161
100.0%
Space Separator
ValueCountFrequency (%)
3712
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46273389
99.9%
Common 28443
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6295721
13.6%
n 4012798
 
8.7%
i 3190450
 
6.9%
a 3106151
 
6.7%
p 3032360
 
6.6%
r 2719969
 
5.9%
l 2239561
 
4.8%
G 2229639
 
4.8%
o 2220022
 
4.8%
u 2212994
 
4.8%
Other values (41) 15013724
32.4%
Common
ValueCountFrequency (%)
- 19523
68.6%
& 5161
 
18.1%
3712
 
13.1%
1 27
 
0.1%
5 10
 
< 0.1%
0 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46301832
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 6295721
13.6%
n 4012798
 
8.7%
i 3190450
 
6.9%
a 3106151
 
6.7%
p 3032360
 
6.5%
r 2719969
 
5.9%
l 2239561
 
4.8%
G 2229639
 
4.8%
o 2220022
 
4.8%
u 2212994
 
4.8%
Other values (47) 15042167
32.5%

bundleId
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
com.loop.match3d
4505172 
1502447854
1186861 
com.tilegarden.match3
805433 
se.ace.fishinc
 
190584
1529614832
 
135974
Other values (13)
497609 

Length

Max length27
Median length16
Mean length15.594941
Min length10

Characters and Unicode

Total characters114180434
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcom.tilegarden.match3
2nd rowcom.loop.match3d
3rd rowcom.loop.match3d
4th rowcom.loop.match3d
5th rowcom.loop.match3d

Common Values

ValueCountFrequency (%)
com.loop.match3d 4505172
61.5%
1502447854 1186861
 
16.2%
com.tilegarden.match3 805433
 
11.0%
se.ace.fishinc 190584
 
2.6%
1529614832 135974
 
1.9%
com.tintash.nailsalon 134457
 
1.8%
1523081624 104315
 
1.4%
com.AppIdeas.LevelUpRunner 62044
 
0.8%
com.kamilbilge.ropesavior3d 53746
 
0.7%
1436213906 32046
 
0.4%
Other values (8) 111001
 
1.5%

Length

2023-07-28T13:07:54.815062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
com.loop.match3d 4505172
61.5%
1502447854 1186861
 
16.2%
com.tilegarden.match3 805433
 
11.0%
se.ace.fishinc 190584
 
2.6%
1529614832 135974
 
1.9%
com.tintash.nailsalon 134457
 
1.8%
1523081624 104315
 
1.4%
com.appideas.leveluprunner 62044
 
0.8%
com.kamilbilge.ropesavior3d 53746
 
0.7%
1436213906 32046
 
0.4%
Other values (8) 111001
 
1.5%

Most occurring characters

ValueCountFrequency (%)
o 15002423
13.1%
. 11665006
10.2%
c 11358488
 
9.9%
m 11033414
 
9.7%
a 6933452
 
6.1%
t 6468367
 
5.7%
l 5800995
 
5.1%
3 5699688
 
5.0%
h 5635646
 
4.9%
d 5507462
 
4.8%
Other values (30) 29075493
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 81774795
71.6%
Decimal Number 20255651
 
17.7%
Other Punctuation 11665006
 
10.2%
Uppercase Letter 484982
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 15002423
18.3%
c 11358488
13.9%
m 11033414
13.5%
a 6933452
8.5%
t 6468367
7.9%
l 5800995
 
7.1%
h 5635646
 
6.9%
d 5507462
 
6.7%
p 4772194
 
5.8%
e 2460244
 
3.0%
Other values (11) 6802110
8.3%
Decimal Number
ValueCountFrequency (%)
3 5699688
28.1%
4 3853536
19.0%
5 2669229
13.2%
1 1761465
 
8.7%
2 1736041
 
8.6%
8 1470920
 
7.3%
0 1323222
 
6.5%
7 1211525
 
6.0%
6 333813
 
1.6%
9 196212
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
A 120298
24.8%
L 91171
18.8%
R 62044
12.8%
U 62044
12.8%
I 62044
12.8%
Y 29127
 
6.0%
S 29127
 
6.0%
D 29127
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 11665006
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82259777
72.0%
Common 31920657
 
28.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 15002423
18.2%
c 11358488
13.8%
m 11033414
13.4%
a 6933452
8.4%
t 6468367
7.9%
l 5800995
 
7.1%
h 5635646
 
6.9%
d 5507462
 
6.7%
p 4772194
 
5.8%
e 2460244
 
3.0%
Other values (19) 7287092
8.9%
Common
ValueCountFrequency (%)
. 11665006
36.5%
3 5699688
17.9%
4 3853536
 
12.1%
5 2669229
 
8.4%
1 1761465
 
5.5%
2 1736041
 
5.4%
8 1470920
 
4.6%
0 1323222
 
4.1%
7 1211525
 
3.8%
6 333813
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114180434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 15002423
13.1%
. 11665006
10.2%
c 11358488
 
9.9%
m 11033414
 
9.7%
a 6933452
 
6.1%
t 6468367
 
5.7%
l 5800995
 
5.1%
3 5699688
 
5.0%
h 5635646
 
4.9%
d 5507462
 
4.8%
Other values (30) 29075493
25.5%
Distinct101
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:54.964164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.2537919
Min length3

Characters and Unicode

Total characters60431235
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.8.22
2nd row1245.34.0
3rd row1245.35.0
4th row1245.34.0
5th row1245.35.0
ValueCountFrequency (%)
1245.35.0 2911851
39.8%
1245.34.0 2424607
33.1%
1.8.46 561931
 
7.7%
2.23.2 217127
 
3.0%
1.3.6 148394
 
2.0%
1.8.55 122181
 
1.7%
1245.33.0 120199
 
1.6%
1.3.9 99689
 
1.4%
1.8.50 81076
 
1.1%
1.8.52 79288
 
1.1%
Other values (91) 555290
 
7.6%
2023-07-28T13:07:55.248398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 14539436
24.1%
5 9085039
15.0%
4 8800350
14.6%
1 7078813
11.7%
2 6687316
11.1%
3 6417318
10.6%
0 5866726
9.7%
8 963425
 
1.6%
6 726302
 
1.2%
9 180678
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45891799
75.9%
Other Punctuation 14539436
 
24.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 9085039
19.8%
4 8800350
19.2%
1 7078813
15.4%
2 6687316
14.6%
3 6417318
14.0%
0 5866726
12.8%
8 963425
 
2.1%
6 726302
 
1.6%
9 180678
 
0.4%
7 85832
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 14539436
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60431235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 14539436
24.1%
5 9085039
15.0%
4 8800350
14.6%
1 7078813
11.7%
2 6687316
11.1%
3 6417318
10.6%
0 5866726
9.7%
8 963425
 
1.6%
6 726302
 
1.2%
9 180678
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60431235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 14539436
24.1%
5 9085039
15.0%
4 8800350
14.6%
1 7078813
11.7%
2 6687316
11.1%
3 6417318
10.6%
0 5866726
9.7%
8 963425
 
1.6%
6 726302
 
1.2%
9 180678
 
0.3%
Distinct2568
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:55.473420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length8.5900159
Min length1

Characters and Unicode

Total characters62892944
Distinct characters69
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)< 0.1%

Sample

1st rowLM-V405
2nd rowAndroid 4.0
3rd rowAndroid 4.0
4th rowAndroid 4.0
5th rowCPH2127
ValueCountFrequency (%)
android 2088521
19.3%
4.0 1973042
18.3%
iphone 1202415
 
11.1%
moto 436623
 
4.0%
ipad 286490
 
2.7%
g 159210
 
1.5%
redmi 94964
 
0.9%
5g 92550
 
0.9%
power 91148
 
0.8%
note 85673
 
0.8%
Other values (2463) 4288555
39.7%
2023-07-28T13:07:55.850800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 4583001
 
7.3%
o 4436334
 
7.1%
0 4287875
 
6.8%
i 3766886
 
6.0%
3477558
 
5.5%
n 3390204
 
5.4%
A 3160341
 
5.0%
M 2704043
 
4.3%
- 2284177
 
3.6%
r 2271314
 
3.6%
Other values (59) 28531211
45.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24122367
38.4%
Uppercase Letter 16210620
25.8%
Decimal Number 14438169
23.0%
Space Separator 3477558
 
5.5%
Dash Punctuation 2284177
 
3.6%
Other Punctuation 2039874
 
3.2%
Open Punctuation 154354
 
0.2%
Close Punctuation 154354
 
0.2%
Math Symbol 8797
 
< 0.1%
Connector Punctuation 2674
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 4583001
19.0%
o 4436334
18.4%
i 3766886
15.6%
n 3390204
14.1%
r 2271314
9.4%
e 1768628
 
7.3%
h 1203381
 
5.0%
t 695559
 
2.9%
a 484582
 
2.0%
l 306474
 
1.3%
Other values (16) 1216004
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
A 3160341
19.5%
M 2704043
16.7%
S 2080213
12.8%
P 1918837
11.8%
G 986748
 
6.1%
L 688236
 
4.2%
F 628492
 
3.9%
T 532965
 
3.3%
N 427259
 
2.6%
U 375414
 
2.3%
Other values (16) 2708072
16.7%
Decimal Number
ValueCountFrequency (%)
0 4287875
29.7%
4 2266875
15.7%
1 1678862
 
11.6%
2 1494379
 
10.4%
5 1446586
 
10.0%
9 964679
 
6.7%
7 665835
 
4.6%
6 642182
 
4.4%
3 595453
 
4.1%
8 395443
 
2.7%
Space Separator
ValueCountFrequency (%)
3477558
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2284177
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2039874
100.0%
Open Punctuation
ValueCountFrequency (%)
( 154354
100.0%
Close Punctuation
ValueCountFrequency (%)
) 154354
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8797
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2674
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40332987
64.1%
Common 22559957
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 4583001
11.4%
o 4436334
11.0%
i 3766886
 
9.3%
n 3390204
 
8.4%
A 3160341
 
7.8%
M 2704043
 
6.7%
r 2271314
 
5.6%
S 2080213
 
5.2%
P 1918837
 
4.8%
e 1768628
 
4.4%
Other values (42) 10253186
25.4%
Common
ValueCountFrequency (%)
0 4287875
19.0%
3477558
15.4%
- 2284177
10.1%
4 2266875
10.0%
. 2039874
9.0%
1 1678862
 
7.4%
2 1494379
 
6.6%
5 1446586
 
6.4%
9 964679
 
4.3%
7 665835
 
3.0%
Other values (7) 1953257
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62892944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 4583001
 
7.3%
o 4436334
 
7.1%
0 4287875
 
6.8%
i 3766886
 
6.0%
3477558
 
5.5%
n 3390204
 
5.4%
A 3160341
 
5.0%
M 2704043
 
4.3%
- 2284177
 
3.6%
r 2271314
 
3.6%
Other values (59) 28531211
45.4%
Distinct168
Distinct (%)< 0.1%
Missing27
Missing (%)< 0.1%
Memory size55.9 MiB
2023-07-28T13:07:56.065585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14643212
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowUS
2nd rowFR
3rd rowUS
4th rowGB
5th rowID
ValueCountFrequency (%)
us 2822649
38.6%
gb 706591
 
9.7%
br 449634
 
6.1%
jp 411060
 
5.6%
mx 400655
 
5.5%
de 361675
 
4.9%
fr 356938
 
4.9%
ca 295789
 
4.0%
au 140159
 
1.9%
ru 130387
 
1.8%
Other values (158) 1246069
17.0%
2023-07-28T13:07:56.385344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 3116680
21.3%
S 3001766
20.5%
B 1202715
 
8.2%
R 1106671
 
7.6%
G 788163
 
5.4%
E 569964
 
3.9%
A 557826
 
3.8%
P 525869
 
3.6%
M 453868
 
3.1%
D 446120
 
3.0%
Other values (17) 2873570
19.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 14643204
> 99.9%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 3116680
21.3%
S 3001766
20.5%
B 1202715
 
8.2%
R 1106671
 
7.6%
G 788163
 
5.4%
E 569964
 
3.9%
A 557826
 
3.8%
P 525869
 
3.6%
M 453868
 
3.1%
D 446120
 
3.0%
Other values (16) 2873562
19.6%
Other Punctuation
ValueCountFrequency (%)
/ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14643204
> 99.9%
Common 8
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 3116680
21.3%
S 3001766
20.5%
B 1202715
 
8.2%
R 1106671
 
7.6%
G 788163
 
5.4%
E 569964
 
3.9%
A 557826
 
3.8%
P 525869
 
3.6%
M 453868
 
3.1%
D 446120
 
3.0%
Other values (16) 2873562
19.6%
Common
ValueCountFrequency (%)
/ 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14643212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 3116680
21.3%
S 3001766
20.5%
B 1202715
 
8.2%
R 1106671
 
7.6%
G 788163
 
5.4%
E 569964
 
3.9%
A 557826
 
3.8%
P 525869
 
3.6%
M 453868
 
3.1%
D 446120
 
3.0%
Other values (17) 2873570
19.6%
Distinct40176
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:56.581234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters80537963
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1380 ?
Unique (%)< 0.1%

Sample

1st row74f9b473fad
2nd row6ad4c88b84e
3rd row743b9849642
4th row6ad933115b2
5th row809f9785bb3
ValueCountFrequency (%)
74fcefce53d 25150
 
0.3%
803711bf2cf 21068
 
0.3%
806c7d76a7f 15817
 
0.2%
74a638e3a27 13065
 
0.2%
808f7c3fa73 12532
 
0.2%
742c17ede61 12206
 
0.2%
7429bbd557c 11762
 
0.2%
805a2657065 11489
 
0.2%
740f8afaadc 11288
 
0.2%
74643d3d2b7 11032
 
0.2%
Other values (40166) 7176224
98.0%
2023-07-28T13:07:56.902740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 6750367
 
8.4%
0 6645485
 
8.3%
8 6632513
 
8.2%
4 6517186
 
8.1%
6 6337531
 
7.9%
a 6285215
 
7.8%
c 4337422
 
5.4%
b 4232209
 
5.3%
f 4213471
 
5.2%
1 4201932
 
5.2%
Other values (6) 24384632
30.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53291572
66.2%
Lowercase Letter 27246391
33.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 6750367
12.7%
0 6645485
12.5%
8 6632513
12.4%
4 6517186
12.2%
6 6337531
11.9%
1 4201932
7.9%
2 4149523
7.8%
5 4061657
7.6%
3 4009384
7.5%
9 3985994
7.5%
Lowercase Letter
ValueCountFrequency (%)
a 6285215
23.1%
c 4337422
15.9%
b 4232209
15.5%
f 4213471
15.5%
d 4163490
15.3%
e 4014584
14.7%

Most occurring scripts

ValueCountFrequency (%)
Common 53291572
66.2%
Latin 27246391
33.8%

Most frequent character per script

Common
ValueCountFrequency (%)
7 6750367
12.7%
0 6645485
12.5%
8 6632513
12.4%
4 6517186
12.2%
6 6337531
11.9%
1 4201932
7.9%
2 4149523
7.8%
5 4061657
7.6%
3 4009384
7.5%
9 3985994
7.5%
Latin
ValueCountFrequency (%)
a 6285215
23.1%
c 4337422
15.9%
b 4232209
15.5%
f 4213471
15.5%
d 4163490
15.3%
e 4014584
14.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80537963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 6750367
 
8.4%
0 6645485
 
8.3%
8 6632513
 
8.2%
4 6517186
 
8.1%
6 6337531
 
7.9%
a 6285215
 
7.8%
c 4337422
 
5.4%
b 4232209
 
5.3%
f 4213471
 
5.2%
1 4201932
 
5.2%
Other values (6) 24384632
30.3%
Distinct96
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:57.075655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.956008
Min length8

Characters and Unicode

Total characters80215868
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAndroid-10.0
2nd rowAndroid-4.0
3rd rowAndroid-4.0
4th rowAndroid-4.0
5th rowAndroid-11.0
ValueCountFrequency (%)
android-4.0 2034520
27.8%
android-11.0 1875148
25.6%
android-10.0 1093025
14.9%
ios-15.5 1052004
14.4%
android-9.0 501272
 
6.8%
android-8.0.0 121712
 
1.7%
android-8.1.0 95199
 
1.3%
ios-15.4.1 77251
 
1.1%
ios-14.4.2 50445
 
0.7%
android-7.0 46642
 
0.6%
Other values (86) 374415
 
5.1%
2023-07-28T13:07:57.366855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 11665006
14.5%
. 7910194
9.9%
i 7321633
9.1%
- 7321633
9.1%
0 7004992
8.7%
1 6770300
8.4%
n 5832503
7.3%
A 5832503
7.3%
o 5832503
7.3%
r 5832503
7.3%
Other values (10) 8892098
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36484148
45.5%
Decimal Number 19689130
24.5%
Uppercase Letter 8810763
 
11.0%
Other Punctuation 7910194
 
9.9%
Dash Punctuation 7321633
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7004992
35.6%
1 6770300
34.4%
4 2418659
 
12.3%
5 2347823
 
11.9%
9 501371
 
2.5%
8 264686
 
1.3%
2 128820
 
0.7%
7 120296
 
0.6%
3 92478
 
0.5%
6 39705
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
d 11665006
32.0%
i 7321633
20.1%
n 5832503
16.0%
o 5832503
16.0%
r 5832503
16.0%
Uppercase Letter
ValueCountFrequency (%)
A 5832503
66.2%
O 1489130
 
16.9%
S 1489130
 
16.9%
Other Punctuation
ValueCountFrequency (%)
. 7910194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7321633
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45294911
56.5%
Common 34920957
43.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7910194
22.7%
- 7321633
21.0%
0 7004992
20.1%
1 6770300
19.4%
4 2418659
 
6.9%
5 2347823
 
6.7%
9 501371
 
1.4%
8 264686
 
0.8%
2 128820
 
0.4%
7 120296
 
0.3%
Other values (2) 132183
 
0.4%
Latin
ValueCountFrequency (%)
d 11665006
25.8%
i 7321633
16.2%
n 5832503
12.9%
A 5832503
12.9%
o 5832503
12.9%
r 5832503
12.9%
O 1489130
 
3.3%
S 1489130
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80215868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 11665006
14.5%
. 7910194
9.9%
i 7321633
9.1%
- 7321633
9.1%
0 7004992
8.7%
1 6770300
8.4%
n 5832503
7.3%
A 5832503
7.3%
o 5832503
7.3%
r 5832503
7.3%
Other values (10) 8892098
11.1%

connectionType
Categorical

Distinct3
Distinct (%)< 0.1%
Missing666
Missing (%)< 0.1%
Memory size55.9 MiB
WIFI
5844929 
3G
1168337 
UNKNOWN
 
307701

Length

Max length7
Median length4
Mean length3.8069147
Min length2

Characters and Unicode

Total characters27870297
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3G
2nd rowWIFI
3rd rowWIFI
4th rowWIFI
5th rowWIFI

Common Values

ValueCountFrequency (%)
WIFI 5844929
79.8%
3G 1168337
 
16.0%
UNKNOWN 307701
 
4.2%
(Missing) 666
 
< 0.1%

Length

2023-07-28T13:07:57.507342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-28T13:07:57.615748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
wifi 5844929
79.8%
3g 1168337
 
16.0%
unknown 307701
 
4.2%

Most occurring characters

ValueCountFrequency (%)
I 11689858
41.9%
W 6152630
22.1%
F 5844929
21.0%
3 1168337
 
4.2%
G 1168337
 
4.2%
N 923103
 
3.3%
U 307701
 
1.1%
K 307701
 
1.1%
O 307701
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 26701960
95.8%
Decimal Number 1168337
 
4.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 11689858
43.8%
W 6152630
23.0%
F 5844929
21.9%
G 1168337
 
4.4%
N 923103
 
3.5%
U 307701
 
1.2%
K 307701
 
1.2%
O 307701
 
1.2%
Decimal Number
ValueCountFrequency (%)
3 1168337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26701960
95.8%
Common 1168337
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 11689858
43.8%
W 6152630
23.0%
F 5844929
21.9%
G 1168337
 
4.4%
N 923103
 
3.5%
U 307701
 
1.2%
K 307701
 
1.2%
O 307701
 
1.2%
Common
ValueCountFrequency (%)
3 1168337
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27870297
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 11689858
41.9%
W 6152630
22.1%
F 5844929
21.0%
3 1168337
 
4.2%
G 1168337
 
4.2%
N 923103
 
3.3%
U 307701
 
1.1%
K 307701
 
1.1%
O 307701
 
1.1%

c1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct50
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
7d3
3758421 
59b
1017069 
cb2
592105 
7b8
439421 
8bd
 
307330
Other values (45)
1207287 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21964899
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcb2
2nd row7d3
3rd row7d3
4th row7d3
5th row8bd

Common Values

ValueCountFrequency (%)
7d3 3758421
51.3%
59b 1017069
 
13.9%
cb2 592105
 
8.1%
7b8 439421
 
6.0%
8bd 307330
 
4.2%
f0f 108166
 
1.5%
fdc 107148
 
1.5%
1ba 106180
 
1.5%
7ca 104280
 
1.4%
82a 99103
 
1.4%
Other values (40) 682410
 
9.3%

Length

2023-07-28T13:07:57.727079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
7d3 3758421
51.3%
59b 1017069
 
13.9%
cb2 592105
 
8.1%
7b8 439421
 
6.0%
8bd 307330
 
4.2%
f0f 108166
 
1.5%
fdc 107148
 
1.5%
1ba 106180
 
1.5%
7ca 104280
 
1.4%
82a 99103
 
1.4%
Other values (40) 682410
 
9.3%

Most occurring characters

ValueCountFrequency (%)
7 4462724
20.3%
d 4417867
20.1%
3 4004498
18.2%
b 2597415
11.8%
9 1105032
 
5.0%
c 1037132
 
4.7%
5 1035916
 
4.7%
8 878831
 
4.0%
2 871274
 
4.0%
a 438234
 
2.0%
Other values (6) 1115976
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12894922
58.7%
Lowercase Letter 9069977
41.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 4462724
34.6%
3 4004498
31.1%
9 1105032
 
8.6%
5 1035916
 
8.0%
8 878831
 
6.8%
2 871274
 
6.8%
1 233420
 
1.8%
0 146746
 
1.1%
6 117468
 
0.9%
4 39013
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
d 4417867
48.7%
b 2597415
28.6%
c 1037132
 
11.4%
a 438234
 
4.8%
f 403487
 
4.4%
e 175842
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 12894922
58.7%
Latin 9069977
41.3%

Most frequent character per script

Common
ValueCountFrequency (%)
7 4462724
34.6%
3 4004498
31.1%
9 1105032
 
8.6%
5 1035916
 
8.0%
8 878831
 
6.8%
2 871274
 
6.8%
1 233420
 
1.8%
0 146746
 
1.1%
6 117468
 
0.9%
4 39013
 
0.3%
Latin
ValueCountFrequency (%)
d 4417867
48.7%
b 2597415
28.6%
c 1037132
 
11.4%
a 438234
 
4.8%
f 403487
 
4.4%
e 175842
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21964899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 4462724
20.3%
d 4417867
20.1%
3 4004498
18.2%
b 2597415
11.8%
9 1105032
 
5.0%
c 1037132
 
4.7%
5 1035916
 
4.7%
8 878831
 
4.0%
2 871274
 
4.0%
a 438234
 
2.0%
Other values (6) 1115976
 
5.1%

c2
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0005896
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:57.946177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3443872
Coefficient of variation (CV)0.46882216
Kurtosis-1.1312811
Mean5.0005896
Median Absolute Deviation (MAD)2
Skewness0.00025090474
Sum36612482
Variance5.4961515
MonotonicityNot monotonic
2023-07-28T13:07:58.064273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 916854
12.5%
5 916324
12.5%
6 915617
12.5%
2 914927
12.5%
3 914608
12.5%
8 914607
12.5%
7 914587
12.5%
9 457874
6.3%
1 456235
6.2%
ValueCountFrequency (%)
1 456235
6.2%
2 914927
12.5%
3 914608
12.5%
4 916854
12.5%
5 916324
12.5%
6 915617
12.5%
7 914587
12.5%
8 914607
12.5%
9 457874
6.3%
ValueCountFrequency (%)
9 457874
6.3%
8 914607
12.5%
7 914587
12.5%
6 915617
12.5%
5 916324
12.5%
4 916854
12.5%
3 914608
12.5%
2 914927
12.5%
1 456235
6.2%

c3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
6b
5832503 
4b
1303645 
79
 
107368
4e
 
78117

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14643266
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6b
2nd row6b
3rd row6b
4th row6b
5th row6b

Common Values

ValueCountFrequency (%)
6b 5832503
79.7%
4b 1303645
 
17.8%
79 107368
 
1.5%
4e 78117
 
1.1%

Length

2023-07-28T13:07:58.194158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-28T13:07:58.299471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6b 5832503
79.7%
4b 1303645
 
17.8%
79 107368
 
1.5%
4e 78117
 
1.1%

Most occurring characters

ValueCountFrequency (%)
b 7136148
48.7%
6 5832503
39.8%
4 1381762
 
9.4%
7 107368
 
0.7%
9 107368
 
0.7%
e 78117
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7429001
50.7%
Lowercase Letter 7214265
49.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 5832503
78.5%
4 1381762
 
18.6%
7 107368
 
1.4%
9 107368
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
b 7136148
98.9%
e 78117
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 7429001
50.7%
Latin 7214265
49.3%

Most frequent character per script

Common
ValueCountFrequency (%)
6 5832503
78.5%
4 1381762
 
18.6%
7 107368
 
1.4%
9 107368
 
1.4%
Latin
ValueCountFrequency (%)
b 7136148
98.9%
e 78117
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14643266
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
b 7136148
48.7%
6 5832503
39.8%
4 1381762
 
9.4%
7 107368
 
0.7%
9 107368
 
0.7%
e 78117
 
0.5%

c4
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9990439
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:58.400387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3452978
Coefficient of variation (CV)0.46914928
Kurtosis-1.1320028
Mean4.9990439
Median Absolute Deviation (MAD)2
Skewness0.00066535603
Sum36601165
Variance5.5004219
MonotonicityNot monotonic
2023-07-28T13:07:58.515977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3 915874
12.5%
5 915719
12.5%
4 915684
12.5%
2 914942
12.5%
7 914813
12.5%
8 914337
12.5%
6 914273
12.5%
1 458202
6.3%
9 457789
6.3%
ValueCountFrequency (%)
1 458202
6.3%
2 914942
12.5%
3 915874
12.5%
4 915684
12.5%
5 915719
12.5%
6 914273
12.5%
7 914813
12.5%
8 914337
12.5%
9 457789
6.3%
ValueCountFrequency (%)
9 457789
6.3%
8 914337
12.5%
7 914813
12.5%
6 914273
12.5%
5 915719
12.5%
4 915684
12.5%
3 915874
12.5%
2 914942
12.5%
1 458202
6.3%

size
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
320x50
5188261 
320x480
1390749 
728x90
597514 
768x1024
 
142453
480x320
 
1842

Length

Max length8
Median length6
Mean length6.2293375
Min length6

Characters and Unicode

Total characters45608923
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row320x50
2nd row320x50
3rd row320x50
4th row320x50
5th row320x480

Common Values

ValueCountFrequency (%)
320x50 5188261
70.9%
320x480 1390749
 
19.0%
728x90 597514
 
8.2%
768x1024 142453
 
1.9%
480x320 1842
 
< 0.1%
1024x768 814
 
< 0.1%

Length

2023-07-28T13:07:58.658787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-28T13:07:58.787787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
320x50 5188261
70.9%
320x480 1390749
 
19.0%
728x90 597514
 
8.2%
768x1024 142453
 
1.9%
480x320 1842
 
< 0.1%
1024x768 814
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 13902485
30.5%
2 7321633
16.1%
x 7321633
16.1%
3 6580852
14.4%
5 5188261
 
11.4%
8 2133372
 
4.7%
4 1535858
 
3.4%
7 740781
 
1.6%
9 597514
 
1.3%
6 143267
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38287290
83.9%
Lowercase Letter 7321633
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13902485
36.3%
2 7321633
19.1%
3 6580852
17.2%
5 5188261
 
13.6%
8 2133372
 
5.6%
4 1535858
 
4.0%
7 740781
 
1.9%
9 597514
 
1.6%
6 143267
 
0.4%
1 143267
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
x 7321633
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38287290
83.9%
Latin 7321633
 
16.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13902485
36.3%
2 7321633
19.1%
3 6580852
17.2%
5 5188261
 
13.6%
8 2133372
 
5.6%
4 1535858
 
4.0%
7 740781
 
1.9%
9 597514
 
1.6%
6 143267
 
0.4%
1 143267
 
0.4%
Latin
ValueCountFrequency (%)
x 7321633
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45608923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13902485
30.5%
2 7321633
16.1%
x 7321633
16.1%
3 6580852
14.4%
5 5188261
 
11.4%
8 2133372
 
4.7%
4 1535858
 
3.4%
7 740781
 
1.6%
9 597514
 
1.3%
6 143267
 
0.3%

mediationProviderVersion
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct35
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
11.4.3
2580423 
11.4.2
2453815 
11.3.3
1252749 
11.4.1
688090 
11.3.2
 
75491
Other values (30)
271065 

Length

Max length13
Median length6
Mean length6.0351501
Min length6

Characters and Unicode

Total characters44187154
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11.2.1
2nd row11.4.2
3rd row11.4.3
4th row11.4.2
5th row11.4.3

Common Values

ValueCountFrequency (%)
11.4.3 2580423
35.2%
11.4.2 2453815
33.5%
11.3.3 1252749
17.1%
11.4.1 688090
 
9.4%
11.3.2 75491
 
1.0%
11.0.0 62432
 
0.9%
11.1.1 57454
 
0.8%
11.3.1 42342
 
0.6%
11.2.0-beta3 33880
 
0.5%
10.3.1 25445
 
0.3%
Other values (25) 49512
 
0.7%

Length

2023-07-28T13:07:58.929987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11.4.3 2580423
35.2%
11.4.2 2453815
33.5%
11.3.3 1252749
17.1%
11.4.1 688090
 
9.4%
11.3.2 75491
 
1.0%
11.0.0 62432
 
0.9%
11.1.1 57454
 
0.8%
11.3.1 42342
 
0.6%
11.2.0-beta3 33880
 
0.5%
10.3.1 25445
 
0.3%
Other values (25) 49512
 
0.7%

Most occurring characters

ValueCountFrequency (%)
1 15515093
35.1%
. 14643266
33.1%
4 5736838
 
13.0%
3 5280181
 
11.9%
2 2583050
 
5.8%
0 207258
 
0.5%
- 42790
 
0.1%
b 42790
 
0.1%
e 42790
 
0.1%
t 42790
 
0.1%
Other values (4) 50308
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29329938
66.4%
Other Punctuation 14643266
33.1%
Lowercase Letter 171160
 
0.4%
Dash Punctuation 42790
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15515093
52.9%
4 5736838
 
19.6%
3 5280181
 
18.0%
2 2583050
 
8.8%
0 207258
 
0.7%
7 4862
 
< 0.1%
5 2461
 
< 0.1%
6 195
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
b 42790
25.0%
e 42790
25.0%
t 42790
25.0%
a 42790
25.0%
Other Punctuation
ValueCountFrequency (%)
. 14643266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42790
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44015994
99.6%
Latin 171160
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15515093
35.2%
. 14643266
33.3%
4 5736838
 
13.0%
3 5280181
 
12.0%
2 2583050
 
5.9%
0 207258
 
0.5%
- 42790
 
0.1%
7 4862
 
< 0.1%
5 2461
 
< 0.1%
6 195
 
< 0.1%
Latin
ValueCountFrequency (%)
b 42790
25.0%
e 42790
25.0%
t 42790
25.0%
a 42790
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44187154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15515093
35.1%
. 14643266
33.1%
4 5736838
 
13.0%
3 5280181
 
11.9%
2 2583050
 
5.8%
0 207258
 
0.5%
- 42790
 
0.1%
b 42790
 
0.1%
e 42790
 
0.1%
t 42790
 
0.1%
Other values (4) 50308
 
0.1%

bidFloorPrice
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
0.01
6797762 
0.05
 
333847
0.1
 
184991
5.0
 
5033

Length

Max length4
Median length4
Mean length3.9740462
Min length3

Characters and Unicode

Total characters29096508
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.01
2nd row0.01
3rd row0.01
4th row0.01
5th row0.01

Common Values

ValueCountFrequency (%)
0.01 6797762
92.8%
0.05 333847
 
4.6%
0.1 184991
 
2.5%
5.0 5033
 
0.1%

Length

2023-07-28T13:07:59.061297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-28T13:07:59.173103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.01 6797762
92.8%
0.05 333847
 
4.6%
0.1 184991
 
2.5%
5.0 5033
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 14453242
49.7%
. 7321633
25.2%
1 6982753
24.0%
5 338880
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21774875
74.8%
Other Punctuation 7321633
 
25.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14453242
66.4%
1 6982753
32.1%
5 338880
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 7321633
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29096508
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14453242
49.7%
. 7321633
25.2%
1 6982753
24.0%
5 338880
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29096508
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14453242
49.7%
. 7321633
25.2%
1 6982753
24.0%
5 338880
 
1.2%

sentPrice
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7521
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.58103632
Minimum0.01
Maximum970.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:59.312372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.02
median0.04
Q30.17
95-th percentile2.48
Maximum970.41
Range970.4
Interquartile range (IQR)0.15

Descriptive statistics

Standard deviation3.807544
Coefficient of variation (CV)6.5530223
Kurtosis5097.224
Mean0.58103632
Median Absolute Deviation (MAD)0.02
Skewness49.618368
Sum4254134.7
Variance14.497391
MonotonicityNot monotonic
2023-07-28T13:07:59.476193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 1527464
20.9%
0.03 1305035
17.8%
0.01 685243
 
9.4%
0.06 286449
 
3.9%
0.05 285112
 
3.9%
0.04 260406
 
3.6%
0.1 206016
 
2.8%
0.07 184843
 
2.5%
0.08 126981
 
1.7%
0.09 120039
 
1.6%
Other values (7511) 2334045
31.9%
ValueCountFrequency (%)
0.01 685243
9.4%
0.02 1527464
20.9%
0.03 1305035
17.8%
0.04 260406
 
3.6%
0.05 285112
 
3.9%
0.06 286449
 
3.9%
0.07 184843
 
2.5%
0.08 126981
 
1.7%
0.09 120039
 
1.6%
0.1 206016
 
2.8%
ValueCountFrequency (%)
970.41 2
 
< 0.1%
592.04 4
 
< 0.1%
588.01 12
 
< 0.1%
490.36 6
 
< 0.1%
475.35 4
 
< 0.1%
441.02 1
 
< 0.1%
425 41
< 0.1%
418.41 1
 
< 0.1%
417.73 1
 
< 0.1%
414.79 1
 
< 0.1%

winBid
Real number (ℝ)

HIGH CORRELATION 

Distinct23008
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1846252
Minimum0.01
Maximum3405.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size55.9 MiB
2023-07-28T13:07:59.619746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.02
Q10.09
median0.51
Q31.54
95-th percentile15.92
Maximum3405.72
Range3405.71
Interquartile range (IQR)1.45

Descriptive statistics

Standard deviation20.694511
Coefficient of variation (CV)4.9453678
Kurtosis919.50718
Mean4.1846252
Median Absolute Deviation (MAD)0.46
Skewness19.921016
Sum30638290
Variance428.26278
MonotonicityNot monotonic
2023-07-28T13:07:59.770745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02 371679
 
5.1%
0.08 311629
 
4.3%
0.01 250291
 
3.4%
0.03 229963
 
3.1%
0.07 203783
 
2.8%
0.18 125999
 
1.7%
0.06 125373
 
1.7%
0.05 124899
 
1.7%
0.1 121913
 
1.7%
0.04 120485
 
1.6%
Other values (22998) 5335619
72.9%
ValueCountFrequency (%)
0.01 250291
3.4%
0.02 371679
5.1%
0.03 229963
3.1%
0.04 120485
 
1.6%
0.05 124899
 
1.7%
0.06 125373
 
1.7%
0.07 203783
2.8%
0.08 311629
4.3%
0.09 118995
 
1.6%
0.1 121913
 
1.7%
ValueCountFrequency (%)
3405.72 1
 
< 0.1%
2767.72 1
 
< 0.1%
2569.97 1
 
< 0.1%
2527.12 3
< 0.1%
2506.77 1
 
< 0.1%
2391.55 1
 
< 0.1%
2282.33 1
 
< 0.1%
2198.79 3
< 0.1%
2072.89 1
 
< 0.1%
2063.88 1
 
< 0.1%

has_won
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 MiB
0
6509155 
1
812478 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters7321633
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 6509155
88.9%
1 812478
 
11.1%

Length

2023-07-28T13:07:59.903964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-07-28T13:08:00.003530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6509155
88.9%
1 812478
 
11.1%

Most occurring characters

ValueCountFrequency (%)
0 6509155
88.9%
1 812478
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7321633
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6509155
88.9%
1 812478
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 7321633
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6509155
88.9%
1 812478
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7321633
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6509155
88.9%
1 812478
 
11.1%

Interactions

2023-07-28T13:07:21.952253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:09.573134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:12.871970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:15.958527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:18.908971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:22.548951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:10.239756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:13.486839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:16.564686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:19.495349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:23.140672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:10.920249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:14.140537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:17.138641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:20.088085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:23.743361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:11.568300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:14.743743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:17.732730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:20.659998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:24.307316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:12.222330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:15.347223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:18.314203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-07-28T13:07:21.359127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-07-28T13:08:00.086458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
eventTimestampc2c4sentPricewinBidunitDisplayTypebundleIdconnectionTypec1c3sizemediationProviderVersionbidFloorPricehas_won
eventTimestamp1.000-0.0000.0000.0830.0200.0340.0320.0280.0360.0390.0230.1950.3690.038
c2-0.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0010.000
c40.0000.0001.0000.0000.0000.0010.0010.0000.0000.0010.0010.0000.0000.000
sentPrice0.0830.0000.0001.0000.5020.0220.0110.0040.0190.0030.0120.0040.0040.004
winBid0.0200.0000.0000.5021.0000.0340.0260.0060.0300.0040.0210.0110.0040.008
unitDisplayType0.0340.0000.0010.0220.0341.0000.2740.0321.0000.0250.7070.1740.1240.154
bundleId0.0320.0000.0010.0110.0260.2741.0000.3261.0000.5800.1880.6150.5040.142
connectionType0.0280.0000.0000.0040.0060.0320.3261.0000.3270.3220.1080.2620.0590.056
c10.0360.0000.0000.0190.0301.0001.0000.3271.0000.5800.4610.4350.5650.212
c30.0390.0000.0010.0030.0040.0250.5800.3220.5801.0000.1040.4130.0640.116
size0.0230.0000.0010.0120.0210.7070.1880.1080.4610.1041.0000.1200.0950.155
mediationProviderVersion0.1950.0010.0000.0040.0110.1740.6150.2620.4350.4130.1201.0000.3840.104
bidFloorPrice0.3690.0010.0000.0040.0040.1240.5040.0590.5650.0640.0950.3841.0000.014
has_won0.0380.0000.0000.0040.0080.1540.1420.0560.2120.1160.1550.1040.0141.000

Missing values

2023-07-28T13:07:26.651318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-28T13:07:33.340230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-28T13:07:44.745489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

eventTimestampunitDisplayTypebrandNamebundleIdappVersioncorrectModelNamecountryCodedeviceIdosAndVersionconnectionTypec1c2c3c4sizemediationProviderVersionbidFloorPricesentPricewinBidhas_won
01656411567773bannerLGcom.tilegarden.match31.8.22LM-V405US74f9b473fadAndroid-10.03Gcb26.06b4.0320x5011.2.10.010.020.880
11656925395488bannerGenericcom.loop.match3d1245.34.0Android 4.0FR6ad4c88b84eAndroid-4.0WIFI7d36.06b6.0320x5011.4.20.010.030.080
21656913751642bannerGenericcom.loop.match3d1245.35.0Android 4.0US743b9849642Android-4.0WIFI7d33.06b3.0320x5011.4.30.010.021.720
31656656319103bannerGenericcom.loop.match3d1245.34.0Android 4.0GB6ad933115b2Android-4.0WIFI7d33.06b5.0320x5011.4.20.010.060.210
41657429389462interstitialOPPOcom.loop.match3d1245.35.0CPH2127ID809f9785bb3Android-11.0WIFI8bd3.06b3.0320x48011.4.30.010.161.910
51656733933530bannerMotorolacom.loop.match3d1245.35.0One 5G UWUS744b742a55aAndroid-11.0WIFI7d36.06b8.0320x5011.4.30.010.021.900
61656764469359bannerAT&Tcom.tilegarden.match31.7.83V350UUS74c69ddbf47Android-10.03Gcb29.06b5.0320x5011.1.10.010.131.470
71657304610451bannerSamsungcom.loop.match3d1245.35.0SM-T227UUS74c110245b1Android-11.03G7d37.06b2.0728x9011.4.30.010.032.100
81656878804685bannerSamsungcom.tintash.nailsalon1.3.6SM-A032MBR80155787fb4Android-11.0WIFIad33.06b8.0320x5011.3.30.010.020.140
91656535501552bannerApple15024478541245.34.0iPhoneRU74d720f8fb3iOS-14.4.2WIFI59b9.0799.0320x5011.4.10.010.020.200
eventTimestampunitDisplayTypebrandNamebundleIdappVersioncorrectModelNamecountryCodedeviceIdosAndVersionconnectionTypec1c2c3c4sizemediationProviderVersionbidFloorPricesentPricewinBidhas_won
73216231656370561373bannerGenericcom.loop.match3d1245.34.0Android 4.0CA74c35ab0debAndroid-4.0WIFI7d36.06b5.0320x5011.4.20.010.820.870
73216241657339264127rewardedSamsungcom.loop.match3d1245.35.0SM-G9650US74e3c063b10Android-10.0WIFI7b89.06b4.0320x48011.4.30.014.0356.300
73216251656665011731bannerSamsungcom.loop.match3d1245.34.0SM-A105FFR745c5b8e16bAndroid-11.03G7d32.06b8.0320x5011.4.20.010.010.020
73216261657569211484bannerGenericcom.loop.match3d1245.35.0Android 4.0US80ef5d9972aAndroid-4.0WIFI7d38.06b2.0320x5011.4.30.010.030.490
73216271657231691950bannerSamsungcom.loop.match3d1245.35.0SM-A705FNGB74ee5fb57a9Android-11.0WIFI7d39.06b8.0320x5011.4.30.010.050.090
73216281657420756251bannerAlcatelcom.loop.match3d1245.35.09032ZUS80825224919Android-10.0WIFI7d33.06b8.0728x9011.4.30.010.031.670
73216291656659060721bannerGenericcom.tintash.nailsalon1.3.6Android 4.0US74ea71ac486Android-4.03Gad31.06b3.0320x5011.3.30.010.020.860
73216301656866120774bannerLGcom.loop.match3d1245.35.0LM-Q730US6aa4701179dAndroid-10.0WIFI7d34.06b8.0320x5011.4.30.010.021.650
73216311657309395726bannerGenericcom.loop.match3d1245.35.0Android 4.0DE7466a2e7714Android-4.0WIFI7d31.06b4.0320x5011.4.30.010.020.080
73216321656473046234bannerSamsungcom.loop.match3d1245.34.0SCV32JP74f2fd4b126Android-7.0WIFI7d36.06b3.0320x5011.4.20.010.010.100